In many fields of technology, it is desirable to use robots with an autonomous behaviour such that they can freely move around a space without colliding with possible obstacles.
Robotic vacuum cleaners are known in the art and usually equipped with drive means in the form of one or more motors for moving the cleaner across a surface to be cleaned. The robotic vacuum cleaners are further equipped with intelligence in the form of microprocessor(s) and navigation means for causing an autonomous behaviour such that the robotic vacuum cleaners can freely move around and clean a space in the form of e.g. a room. Thus, these prior art robotic vacuum cleaners have the capability of more or less autonomously vacuum clean a room, in which furniture such as tables, chairs and other obstacles such as walls and stairs are located. These robotic vacuum cleaners have navigated a room by means of using structured light, such as e.g. line laser beams, to illuminate obstacles to be detected and registering laser light directly reflected from the obstacles back towards the cleaner in order to determine where the obstacles are located in the room. Images are continuously captured by a camera of the obstacle detecting device of the robotic cleaning device, and distance to the illuminated obstacle such as a wall or a floor can be estimated by detecting the directly reflected laser line in the captured images and using trigonometric functions based on the known position of the cleaner, such that a 3D representation of the room subsequently can be created relative to the robot cleaner. In order to detect a distance to an illuminated object, the structured light source is usually arranged at a known distance, a so called base line, from the camera or the like on the robot cleaner. In addition the structured light source is preferably arranged at a known angle to make sure that the reflected light line of the structured light source is within the field of view of the camera.
For calculating or estimating distances between the robot cleaner and objects/landmarks a trigonometric formula or algorithm is used, as mentioned above. In these algorithms a fixed parameter for value of the known angle at which the structured light source is arranged and a further fixed parameter for the length of the base line are used. These parameters are usually determined by tests in the factory for each robot cleaner after their production. Alternatively these parameters may be pre-set in the processing unit comprising the algorithm during the production.
A problem is that the actual length of the base line and/or the actual angle at which the structured light source is arranged can change over time due to temperature changes within the robot cleaner, due to vibrations for example during transport, changes in the material in which the structured light source is embedded, etc. In particular changes in the actual angle at which the structured light source is arranged may occur in errors when distances are estimated using the obstacle detecting device and a trigonometric algorithm. It follows that measurements performed by using the camera and the structured light source are in some cases not accurate or they may change over time. In such a case the robot cleaner needs to be checked and verified so that the parameters can be calibrated/adjusted.